Dynamic Measurement and Equity Analysis of Walking Accessibility in Primary Healthcare Institutions Under Diverse Supply–Demand Scenarios: Evidence from Shenyang

The walking accessibility of primary healthcare institutions (PHCIs) is a pivotal determinant of health equity. However, prior studies often lack a comprehensive assessment that integrates the spatiotemporal dynamics of both multi-faceted supply and multi-scenario demand. To bridge this gap, this study develops an enhanced two-step floating catchment area method (2SFCA-MSD) that concurrently incorporates multiple types of service supply and multiple temporal demand scenarios to quantify PHCI walking accessibility, with equity evaluated using the Gini coefficient and Lorenz curve. The results indicate that: (1) Both supply and demand exhibit pronounced spatiotemporal inequalities. (2) Walking accessibility varies substantially across scenarios; Health services for vulnerable groups (Service B) exhibit the highest walking accessibility across all three supply scenarios, while the morning work scenario demonstrates the best walking accessibility among the four demand scenarios. (3) Gini coefficients exceeding 0.5 across all scenarios reveal severe resource allocation inequity. By establishing a dynamic supply–demand integration framework, this research advances methodological precision in accessibility evaluation, uncovers critical spatiotemporal mismatch patterns, and provides actionable insights for optimizing PHCI planning to promote spatial justice in urban health.

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Publication Details

Journal
ISPRS International Journal of Geo-Information
Published
2026-01-13
DOI
https://doi.org/10.3390/ijgi15010040
Primary Topic
Urban Transport and Accessibility
Type
article
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article

Dynamic Measurement and Equity Analysis of Walking Accessibility in Primary Healthcare Institutions Under Diverse Supply–Demand Scenarios: Evidence from Shenyang

Cui Qiao, Enxu Wang, Hao Xie, Yang Li et al.
ISPRS International Journal of Geo-Information
Urban Transport and Accessibility
article

Dynamic Measurement and Equity Analysis of Walking Accessibility in Primary Healthcare Institutions Under Diverse Supply–Demand Scenarios: Evidence from Shenyang

Cui Qiao, Enxu Wang, Hao Xie, Yang Li, Shasha Li
article en

Abstract

The walking accessibility of primary healthcare institutions (PHCIs) is a pivotal determinant of health equity. However, prior studies often lack a comprehensive assessment that integrates the spatiotemporal dynamics of both multi-faceted supply and multi-scenario demand. To bridge this gap, this study develops an enhanced two-step floating catchment area method (2SFCA-MSD) that concurrently incorporates multiple types of service supply and multiple temporal demand scenarios to quantify PHCI walking accessibility, with equity evaluated using the Gini coefficient and Lorenz curve. The results indicate that: (1) Both supply and demand exhibit pronounced spatiotemporal inequalities. (2) Walking accessibility varies substantially across scenarios; Health services for vulnerable groups (Service B) exhibit the highest walking accessibility across all three supply scenarios, while the morning work scenario demonstrates the best walking accessibility among the four demand scenarios. (3) Gini coefficients exceeding 0.5 across all scenarios reveal severe resource allocation inequity. By establishing a dynamic supply–demand integration framework, this research advances methodological precision in accessibility evaluation, uncovers critical spatiotemporal mismatch patterns, and provides actionable insights for optimizing PHCI planning to promote spatial justice in urban health.

ISPRS International Journal of Geo-InformationVol. 15(1)
Northeastern University (CN)
Openalex Percentile: Top 91%
Urban Transport and Accessibility
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Dynamic Measurement and Equity Analysis of Walking Accessibility in Primary Healthcare Institutions Under Diverse Supply–Demand Scenarios: Evidence from Shenyang — Cui Qiao, Enxu Wang, et al. · ISPRS International Journal of Geo-Information (2026) | TGRS Research Map | TGRS